{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "52e2e3fe-e71f-42f7-8986-ce6f5daa7c36",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Solarize_Light2', '_classic_test_patch', '_mpl-gallery', '_mpl-gallery-nogrid', 'bmh', 'classic', 'dark_background', 'fast', 'fivethirtyeight', 'ggplot', 'grayscale', 'seaborn', 'seaborn-bright', 'seaborn-colorblind', 'seaborn-dark', 'seaborn-dark-palette', 'seaborn-darkgrid', 'seaborn-deep', 'seaborn-muted', 'seaborn-notebook', 'seaborn-paper', 'seaborn-pastel', 'seaborn-poster', 'seaborn-talk', 'seaborn-ticks', 'seaborn-white', 'seaborn-whitegrid', 'tableau-colorblind10']\n"
     ]
    }
   ],
   "source": [
    "from selenium import webdriver\n",
    "from time import sleep\n",
    "import pandas as pd\n",
    "from io import StringIO\n",
    "from functools import partial\n",
    "import matplotlib.pyplot as plt\n",
    "from selenium.webdriver.support import expected_conditions as EC\n",
    "from selenium.common import NoSuchElementException\n",
    "from matplotlib import style\n",
    "\n",
    "print(plt.style.available)\n",
    "%matplotlib inline\n",
    "\n",
    "driver=webdriver.Edge()\n",
    "\n",
    "url='https://quote.cngold.org/gjs/swhj_zghj.html'\n",
    "driver.get(url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "99701335-daaa-423e-9b00-6c2d29596eb5",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "try:\n",
    "    next_page=driver.find_element('partial link text','下一页')\n",
    "    next_page.click()\n",
    "except NoSuchElementException:\n",
    "    print(\"Hello\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7d652a67-e1dc-48e9-a645-87379ce55fe0",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "string_list=[]\n",
    "\n",
    "i=0\n",
    "\n",
    "while i==0:\n",
    "    string=driver.find_element('id','goldTable').text\n",
    "    string_list.append(string)\n",
    "    #driver.refresh()\n",
    "    try:\n",
    "        next_page=driver.find_element('partial link text','下一页')\n",
    "        next_page.click()\n",
    "    except NoSuchElementException:\n",
    "        break\n",
    "    #sleep(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2491d94f-70c6-4c9c-80cb-dc6616e4fe56",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "driver.quit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "27abcef1-afa9-45da-88a0-4c2c916c7581",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "fun_read_csv=partial(pd.read_csv,sep=' ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0dcd3a43-504b-45e7-9b12-32f20087f4e8",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "io_list=map(StringIO,string_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e97bd782-53a1-467f-82b6-15e8a2a78445",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "df_list=list(map(fun_read_csv,io_list))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "05a4e4f0-8e65-4591-a531-644c79e74038",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "df_gold=pd.concat(df_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "27a714c3-2208-4447-afd1-fe7454040caf",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "df_gold=df_gold.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "549958ea-f88c-45d1-81f3-aa0c99ce1ec9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>名称</th>\n",
       "      <th>价格</th>\n",
       "      <th>单位</th>\n",
       "      <th>纯度</th>\n",
       "      <th>手工费</th>\n",
       "      <th>涨跌</th>\n",
       "      <th>更新日期</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>447.8</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>跌</td>\n",
       "      <td>2023-06-27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>448.1</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>涨</td>\n",
       "      <td>2023-06-26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>447.5</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>跌</td>\n",
       "      <td>2023-06-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>449.5</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>涨</td>\n",
       "      <td>2023-06-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>447.7</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>跌</td>\n",
       "      <td>2023-06-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3075</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>361.0</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>涨</td>\n",
       "      <td>2012-02-24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3076</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>360.1</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>涨</td>\n",
       "      <td>2012-02-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3077</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>356.1</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>涨</td>\n",
       "      <td>2012-02-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3078</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>353.0</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>涨</td>\n",
       "      <td>2012-02-20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3079</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>352.0</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>涨</td>\n",
       "      <td>2012-02-17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3080 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            名称     价格   单位     纯度  手工费 涨跌        更新日期\n",
       "0     中国黄金基础金价  447.8  元/克  99.9%    0  跌  2023-06-27\n",
       "1     中国黄金基础金价  448.1  元/克  99.9%    0  涨  2023-06-26\n",
       "2     中国黄金基础金价  447.5  元/克  99.9%    0  跌  2023-06-25\n",
       "3     中国黄金基础金价  449.5  元/克  99.9%    0  涨  2023-06-23\n",
       "4     中国黄金基础金价  447.7  元/克  99.9%    0  跌  2023-06-22\n",
       "...        ...    ...  ...    ...  ... ..         ...\n",
       "3075  中国黄金基础金价  361.0  元/克  99.9%    0  涨  2012-02-24\n",
       "3076  中国黄金基础金价  360.1  元/克  99.9%    0  涨  2012-02-23\n",
       "3077  中国黄金基础金价  356.1  元/克  99.9%    0  涨  2012-02-22\n",
       "3078  中国黄金基础金价  353.0  元/克  99.9%    0  涨  2012-02-20\n",
       "3079  中国黄金基础金价  352.0  元/克  99.9%    0  涨  2012-02-17\n",
       "\n",
       "[3080 rows x 7 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_gold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f74a3bc5-fea5-4bc3-a201-b5b2f8402aec",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>名称</th>\n",
       "      <th>价格</th>\n",
       "      <th>单位</th>\n",
       "      <th>纯度</th>\n",
       "      <th>手工费</th>\n",
       "      <th>涨跌</th>\n",
       "      <th>更新日期</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1297</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>2781.0</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>涨</td>\n",
       "      <td>2019-04-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1351</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>2860.0</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>平</td>\n",
       "      <td>2019-01-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1352</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>2860.0</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>平</td>\n",
       "      <td>2019-01-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1353</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>2860.0</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>平</td>\n",
       "      <td>2019-01-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1354</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>2860.0</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>平</td>\n",
       "      <td>2019-01-24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1355</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>2860.0</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>平</td>\n",
       "      <td>2019-01-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1356</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>2860.0</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>平</td>\n",
       "      <td>2019-01-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1357</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>2860.0</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>平</td>\n",
       "      <td>2019-01-21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1358</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>2860.0</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>平</td>\n",
       "      <td>2019-01-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1359</th>\n",
       "      <td>中国黄金基础金价</td>\n",
       "      <td>2860.0</td>\n",
       "      <td>元/克</td>\n",
       "      <td>99.9%</td>\n",
       "      <td>0</td>\n",
       "      <td>平</td>\n",
       "      <td>2019-01-17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            名称      价格   单位     纯度  手工费 涨跌        更新日期\n",
       "1297  中国黄金基础金价  2781.0  元/克  99.9%    0  涨  2019-04-25\n",
       "1351  中国黄金基础金价  2860.0  元/克  99.9%    0  平  2019-01-29\n",
       "1352  中国黄金基础金价  2860.0  元/克  99.9%    0  平  2019-01-28\n",
       "1353  中国黄金基础金价  2860.0  元/克  99.9%    0  平  2019-01-25\n",
       "1354  中国黄金基础金价  2860.0  元/克  99.9%    0  平  2019-01-24\n",
       "1355  中国黄金基础金价  2860.0  元/克  99.9%    0  平  2019-01-23\n",
       "1356  中国黄金基础金价  2860.0  元/克  99.9%    0  平  2019-01-22\n",
       "1357  中国黄金基础金价  2860.0  元/克  99.9%    0  平  2019-01-21\n",
       "1358  中国黄金基础金价  2860.0  元/克  99.9%    0  平  2019-01-18\n",
       "1359  中国黄金基础金价  2860.0  元/克  99.9%    0  平  2019-01-17"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_gold.query(\"价格>1000\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "90d9c6c3-33e8-41c7-ae2b-7b484c547305",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "df_gold['Price']=df_gold['价格']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "57437fd9-8961-4aa0-a199-0bbd2e0a3041",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "df_gold['date']=pd.to_datetime(df_gold['更新日期'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "624e8049-ccb0-4a98-a6e7-2056515a801c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "df_gold.loc[df_gold['Price']>1000,'Price']=df_gold['Price']/10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f210e991-7a09-4d1f-94df-8a863e569fb5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    3080.000000\n",
       "mean      321.004968\n",
       "std        63.232176\n",
       "min       218.000000\n",
       "25%       267.000000\n",
       "50%       315.150000\n",
       "75%       386.200000\n",
       "max       455.500000\n",
       "Name: Price, dtype: float64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_gold['Price'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b5130ba6-7cba-4808-9b18-62bf244d4811",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1b4f48d6eb0>]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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EX0DCG6v2wBeQ9NuXLj4Bg8vzMzjCvoHlAURERFlIi7MEobN7gPHsf57TioN1ajZVC061BvQrNxwCoLbNYlN6QIECILOlE4oC+PxqoFrb6EG7R82SV5a6MLSCAWt38C+ZiIgoC8lyZ6CqlQqElwd0+NTA57m31VWVtLpILeDN9GnxbJEtv4Y7n/wUAPSAFQCGVxZkajh9DoNWIiKiLKTo2VVDTWtYeYDbG4Qkd5YAhDeml7MkWMu0bAlao6kaWpzpIfQZDFqJiIiyUGcda/SMaZ7TCp9fwqG6zglX2tKvGplRa4j59yDJMlrafdhd05Kh8XQ6c9awTA+hz2BNKxERURaSTZnWyNvznTYAwHNvbdevC594JTFoBWDOOAeCEm785Yf65WfuPj3q0qnpYhGZP+wu/qaIiIiykLE3a7RMa75TzTsdMrS2au8ImHq35npNa4dPnfjU4vbr19XUd5i22X+0LaVjiLUELyWOQSsREVEWMta0RkuY5oUyrZKs4MKTRgMA3vx0L37w6Ef6NrleHhAMlUt8tKlGvy48SF36wnp4/albWUxb2awoTz1e06sq9NuOGz8gZY/bHzFoJSIiykJ6yysAU8eUR9yuZVoBwGaL/nHOLJ+q1ZRpNS+6oABYt+OofvmDjYdw7bL3k/bY2kS5y+aPwx2XHYt8V+dxc9otSXucXMCglYiIKAvJigIBaqb1yrPH47Efnmy63eXoDH4sMZZvzfFEq85YHuD2RmZVi/I6V6P6z/oDSX3szdUNAIAX//0Vpowuh9vT+fgOBq0J4UQsIiKiLKQoasAKqJN1ClzmPJPTboEYWngg1kSiXC8P0LR1dAatXr8Ucfsr7+2CzSrCIgp6SYGiKPrvvzd+/8Y2ANBXwDKWIlQUOXu9/1zSo0yrJEm48sorsWTJEv26zZs345JLLsGMGTMwf/58LF++3HSf119/HQsWLMD06dOxaNEibNy4sXcjJyIi6ocURcFbq/fiw02HEC9mEgQBeaESAUusoJXlAQDU34NfCxp9kZnW2iYPfvnKJjz0p40IhmpQU/W704LXy88YhwXHD0/JY/RXPQpan3jiCaxfv16/3NLSghtuuAEXXngh1q1bhwceeAAPPvggvvjiCwDA2rVrsXTpUixbtgzr1q3DBRdcgJtvvhkejyc5z4KIiKifaGz14bUPv8b+2vYuW1Zpda2iKODH35sZcTszrar9te246eEPUdfsiZppNdLahsly3M167ORpQwAAp88Yqq9gRt2T8G9r9erVWLFiBc466yz9uhUrVqCkpATf+c53YLVaMXfuXJx//vl4+eWXAQDLly/Hueeei5kzZ8Jms+Hqq69GaWkp3n777eQ9EyIion5ASiBacjo6g9axQ4rxzN2nm27P9UTrlNFlpst7j7R12SkgYCgPSIXTZgzF03efBpuVAWuiEqppbWhowI9//GM8+eSTeOGFF/Trd+3ahfHjx5u2raqqwl//+lcAQHV1NS666KKI23fs2JHQYEVRSHoDYEvoW46F33Yyjscie/BYZBcej+yRrGMRlGS88t4ufOuUMfoiAYB6SnrF+oOmba1xghutLEBRom8niNGvb27zweMPYnB5fk+fQsZ151iErxDW4vbBH4z/pSAYul20CHF/9z2h7c/az+bBp+s9qttBqyzLuOuuu3DNNddg4sSJptvcbjdcLpfpOqfTiY6Ojm7d3l1lZflJKYqOpqjI1fVGlBY8FtmDxyK78Hhkj94ei007j2LFZwdQWuzCd78xSb9+41dH8f7n5qC1tDR2YPl1Tau6v90NuOjMCRG35xc4o97/6gfehawAbz68sKdPIWvEOxbh5RXegKLXrHZ1n6KiPOS7bHG3TVS8Y9kfpPo9qttB6+9//3vY7XZceeWVEbe5XC60tZmb9Xq9XuTn5+u3e73eiNtLS0sTGmxjozslmdaiIhdaWz2QpBQVsFC38FhkDx6L7MLjkT2SdSxaWtXPRJ83gKamzr6hjc2RyRzj7bEMLc+Lul1Liyfq9Vos1519Z6vuHIuOsPZWbo8fPn8Ql86vwl/er467/8YmN/zexINWWVZQ3+JBZWkevvfzd0239eXfdzzhxyJVwXm3g9Z//OMfOHr0KGbNmgUAehD67rvv4u6778aqVatM21dXV2PcuHEAgHHjxmHXrl0Rt59yyikJDVaWlZQVlUuSrJ8SoMziscgePBbZhccje/T2WBjva/y5pd0Xd9tw+U4r3N4gFp40Oup2G3fWYczgom6No6+Kdyx8YZOuAgEJXr8EWzdOY/sDEoK2xPuo/mVlNd5Zux9P3XVaxG394fcdT6rfo7pdfPDOO+9gw4YNWL9+PdavX4/zzjsP5513HtavX48FCxagvr4eL7zwAgKBANasWYM333xTr2O9+OKL8eabb2LNmjUIBAJ44YUX0NDQgAULFqTsiREREWUr2bBEq36drOD5t81zPYYOiJ+xunR+FSpLXDFnob+1el9Ot73S2ktpduxvhiQrGDesGL+4YQ5+du1szJ08MOp9120/GvX6rmzf2wQgsjSBei8piwuUlpbiueeewwMPPIDHHnsMZWVl+MlPfoI5c+YAAObOnYv77rsP999/P2pra1FVVYWnn34aJSUlyXh4IiKiPkWbmW6seGto7SyjW3rdbOyuaY2Y/R7u5GlD9BZKmqED8tHS7ke7JwAACATkmCsvJauBfrbyB81Ba029G8UFdgyvLNCf94CS6HWYL/9nJ86YOSzhx/SEuhOw3Vjy9ThoXbZsmeny1KlT8corr8TcfuHChVi4sO8XfBMREfWW1tXqtQ+/xrlzRwEAPtpcAwC457vHYeiAAgwdUNCjfS+97gQ0tnpx55OfAlCzjbGC1roWLypjBG19naIo8AciT1VPHVNuCtQHleXF3EdQkhPupar1gWWmNfn6V88FIiKiPsDYA1Q7fb9tTyMAwG7t/Xr0xqDMazhFXt/swcoNnd0J2tx+9Fdaayt7WNuqaWPKTZdnHxO9PAAAXvhXYq05gc4VtzhpMvkYtBIREaWZsc508UMrsX1vI46fVAkAGDmosNf7N3baMS5bevfvVuOPK3bqlwP9eGKQtmwrwqofJowoMV0WQwG+3Sri4VvmoWposX7bp1uPJP64od8pM63Jx6CViIgozcLnRu2rbYc/IKO4wJ6U/bsM5QAeX+wVoMKb7/cnWmlAeIlArN6rVouI0kIHLjp1TFIe//HXtpguP3lHYh2TKBKDViIiojQLn9FfmGdTa0970GIpGrvNggtPHg0A6IgTtEar+UxUq9uPLV839Ho/yRbeOUAjxph4pnVqCJ9A1dPuC/tqzf3rnfakzH3PaQxaiYiI0iw8MBIEJDVoBYBvzB4BoKtMa/TALhGPv/YFfvWXzahr9vR6X8nU2Gpe1OjRW0/CXd+eEXXbe787E7ddPA0AUFLoANBZC1vfw+dVVuTo0f0oNgatREREaRYMOy3f1hHAyg2Hkhq02qwiLKIAjy92YJqMmtbm0III//271b3eVzI9HzaJqijfjkkjo6/EWTWsGPlOtWxgcHk+fvn9E7Hku8cBQNzfXzjjcW1sjVwognqHQSsREVGaBSVzpvXV0JKi4X1Fe0MQBLgcVrTE6RCQjKA1W/u8zpwwoMf3LStywhbq4hDtmGzYWYdDde0R17u9sbPa1HsMWomIiNIsZjukJE84z3NY8cHGQwAis7tOuyUpQWt9i7frjdLsaLMH765XW3v1NHutlQf4w35Hh+rdeOJvW/A/L6yLuI87tKDDGcclvigBdY1BKxERUZoFY7RD2n80MnvXG3MmD9Q7BPgNE5P++4oZsFvFftvyaqthYthPvjcT13xzYsL70ILWg2HH5KfPrAUQmS0HALdXDVpHDOrZwhAUH4NWIiKiNAvPeqZKvtOmL2RgDLLGDi2GzSpGZBET1dNJSqlmXMVq6ICCiKVuu8MeytBqpRtAZCeB+5//DK2G8oumNrWO1biAwZzJA/HckvkJPz5FYtBKRESUZkFJQXmRA88tmY9ZodrLc04YgWf/+/SkPo4gdC4ZqzW7v/2SabBaRFitFjS1evGXldWQ5J4Fr7trWpM11KT692f7e70PmzUyRNq4s850eX9tO25//BPUN3sQlGT87h/bAJh7wd5w/uRej4VUDFqJiIjSTJJlWELZQC2jV1LgSPqkJlEUDJlWNTDVspB2q4hVW4/gnbX7sb+2Z2UJHr954lG6MshdOdzQ0et9GLO12u8wVsvWu3+3Gh9uqol6X0oe/laJiIjSpL7FA0VRIEmKHthYLWqg6nQkr92VRhAEPdDSMq2W0BKvxkzin9/bhc3V9Qnv/8V3vjJdDu8/219oZQHb9jbG3KYhyoS0EZWsbU0mBq1ERERpcKSxA3f/djXWfFmLoCTDKmpZVfV/uzUVQasacAWCMvaETuVrwbLNkA2sPtiCF97ZEXUf3bH4vEkAgJse/lCfjNQfaM9Lq54wZlPDbQwL+n9xwxzcfcVxKRtbLmLQSkQZF5TkHtfUEfUVTaEVmmrq3QhKil4eoMWuqTilrC1Z+tbqvXj6n18C6Ky3lMLOdbe0x+7nGsuoQYUAzGMPn23fl2m/v/AM8vSqiohtaxvVkoQ5kwcCAAaV5SHPyaVbk4lBKxFl3A3/9wEeeXVzpodBlFJakGgRBUiSDEuoLABC5On6ZNFKZPcdadOvK863A1Czq0b2Hjz+sMoCjB1SZKrFjdXOK53KQ0uonnfiqF7tRwx9owjvGhBv4YKBpXm9ekyKjV8BiCgrbN/XlOkhEKWUlq0TRQFBWdHLA7RwLxVBq5YpNIZcohh9spe9B034JUmG1SLCuMdsqGutLM3DsAEFWHTKmF7tR8+0hgWtY4cWx7wPzxqlDjOtREREaWCcCBUMBXtAZzY0pUGrIebSJmK5wiZ+9eTxA5ICq0UwZVqlKE3300mSZew62IxJo8p6vS8twNeO3eByNYs6qCwPN14wWb9sLI/w+pO3FC+ZMWglIiJKA2Om1dg9QAjlKcUkt7sCOgNixRC1aoGY024+2dqT8gB/QILNaoExeesPZjZo8wdkBCUFJQX2Xu9L+10poWNX4LLpNasnHDMQJQVqGYLx0MVqi0W9x6CViIgoDbRsXVBScLTZY6hpVf9TkPxoR8uAbt3T2apJC44njSw1bWvrQfcCf0CCw24xZVp9Gc40Hm1SV+lKxsS2zvIAtUTgYJ0bQ8rz9du1JXK15XBPmjoYF8wb1evHpegYtBIREaWBlml9/aOvUVPvjigPSEWGLlb9KgBc9Y0JpssOe+IhgS8gwWETTZlGbyCzQesvX9kIoLP/bW+IoV+JJMtoaPHC4wtiZKhjAqDW9ALQVzW79txJKMzrfYaXomPQSkRElAZS2AQlLeA554SRmDVhAEYOLIx2t16JF7YZM6ujBxdi96FWHG32JLR/X0CG3ZbaTOuzb32Ja5e9bypxiMftVVfpsiQh02oxZFq152VsY6UN6epzJuGpu07r9eNRfAxaiYiI0iB8Vn2LW+2LWlrowPe/NTUlE7EscTKtGkGAfsr7tQ92J7R/n1+Cw2YxZVp9Scy07q9tw6otRwCotaqJsHbjuXfFWNOqfemwip3HadIotcTC6bBw6dY0YMsrIiKiNAjvX9rc7kv5Y3YVCN9+yTQMKHHh35/tBwBs3dNg6mzQFbU8wGLK6CZz9vzDr27Sf273BOCwd7/uNhmZVsHQ8ioYamVl/CJw0Sljcdas4SmZREeR+LWAiIgoDbTJOprS0MzzVDIGrVecOQ6P3naS6fZpYyswuDwfllD20OOTsPNAc7f2/fEXNXogaSx9eO/zg/rP/oCE5nYfFEXp9ul9I6chSG33JLY8bDICSYuh5ZXWystiqJUVRQHFaTiOpGLQSkRElAZByRy03vytqSl/TKshaB1eWYCiGJOEjNnDTdX13dr382/vAAA4bJaIgFzz+Gtf4I4nVuGRv2zG9x/5yHTb0aYOfLjpUNzHmDamc7nUdm9iQWsykp/6iliyotcgJyODSz3D3zwREVEaBMMCO2051VRyGFa5soixP/K17KEoCNhcXd9lVtRYn2u3iqaAfGBZ5zKm2/aqK91t29MYUev6u39swx/e+QqBeH1dhc4lWd0ZyLQaF2forGllKUCmMGglIiJKg4AhsBs2ID/OlslTXuTUf47X/kqr3Rw+sAB1zV7UNHTE3a8xszq4PF+/7LRb4nYsMGrtUCeieXyxg1ZJklHgskMA0BHqCtBdycy0SrKCoNS5ohllBoNWIiKiNDAGemfMHJaWx3Q5Oudbxwu29h5uBaDO1reIAnbsa4q7Xy3reMP5x2DkoEI90+qwWSK6JBgZM7JuT9C0r2gCkgybVVRXEYuzXTTJybSq/8uKAklmeUCm8TdPRESURHuPtOKr/eag74m/bcGKdQcAqEuBnjp9aNrHZYnTbF8LaK0WES6HFV5//KymHCof0Hq9aoFcYZ7NFFwOLs8z3a8u1Ad29bYjermAFgxGoy53K0AUBf0xu1JaqJYTDCh1dWv7eEw1rTIzrZnGoJWIiCiJfvbCejz0p42m6zbsrAOgZj5/ccOctI5HWxkqXrClBZ1lhQ7YrGLMiVWazklJ6j7nTR2Ea86ZiOPGD9CD0EBQ0pdU1Tz40gYAwMZdnZO94mVQg5IMi0WEKAhQusi0anW4A4qdmDt5kKmet6dsod/L1zWt+u8kGSttUc8waCUiIkqC37+xDdcuez/uNsMrC1DgsqVpRCo9GxonaNVO6d+0cApsFtFUfxsuKMkRWUeLKOLkY4fAYhH1fS1fuTsiIC3MsyEQlLF+x9GIx47+WAqsogBRVFelimXZS5/juodWYvehFri9QVOrrN4oDE2W+8vKajz71nYA8Se0UWrxN09ERJQEa7+s7XIbWwaydFqv1ngTsbRa09Ki+JnWDm8AN/zfB/hky+Go+7QYak/fNfRr1YwZXIRPtx42Xaf1P401LqtVzbTGKw/YebAFAPDF7gYcqndj58HmmNsmwmGzmOqCgfi/R0otBq1ERERpkolJPPZQ0BovQ6it1uWwWWC1ihHtuTSvffQ1AGDjTvX0viVsslNXwWVQVvROBZp45QFevwSrJf5ELGN7Lm01rkN17pj7TFRlSe9rYyk5GLQSERGlSaIz4JPBpgetsTOEE4aXAFAD3HiZ1pUb1MUA/KHeqvEyrU67BZNGluq3VZa6EAx1AzD6nxfWxVztqq7Zg9JCR9ya1g821nQ+fiiTbe9i+dpETBhRov986vQhSdsvJc7a9SZERETUUy/8a7v+c6wMZirZ9Rn+sYPWb508BmfOGg5BELqsaQWA5nYfAETUjlosgn66P89pxdihxbj6nIkQAPzp3V3wB2Q8/eaXEfvbdbAZM8YNiLjeF5BQlGeP2j1g18FmFDR78fzbnb9fr0/tenDVNybGHX8izjp+uN75IdoYKX0YtBIREaXQR5s7azjDl3JNB72mNU7fUlEU9BW6utM9QFsQoChsVS9RFPSJVV6fBJfdggGh0+tWi4CmNp++7fe+MQEvvvMVgOhZYEVR4A/IcNgtEAVEBK1LX1gfcR8tYztrYvKCS2NmmO2uMovlAURERGnSVTCYClrQ2N2AqzuZVk1hnrkTgkUQoACoPtgCr18yZWKtFhFtHnUVLFEQMHN8Z2BprLfVAvugpEBWFNijLC6wZtuRqOPp8AVhEQW9Y0Iy5DvT2+2BYmPQSkRElCbBDNS0Xnn2ePzw4mmwd7NvqS3ORKxw4ZO7tBKEX7z0OWRFQWFeZybWahHR6lYzoXdfMQNOu9Vwm3q/ww1u3PB/H+Cr/U163azDZoEoiqbWWH96d1fU8fj8EqxJrGcF2C0gmzBoJSIiSpNMlAc47VYcW1XR7e2tccoDivLiZx3DA7xKw6pUVougP/+SAjtsVhFLF58AoLMHa029Out/d00r/AF1W7tNhM0iIBhUou7XyOuXkjoJSzNrgpoVVpD+Lx3UiUErERFRmmQiaE1UrJrW//rNKrR2BDB+WHHM+4ZnXgcY2kUZ233lhU65O0PZ3/ClXFdtOYyHX90EQJ1IZjWULLy7/gC+rmmN+vhefzAlQeuQinz1B8asGcWglYiIKAkc3ViFadrY7mc8MyVWTas2iWry6LKY9y0tcJguGxvz2wxBq1brqpUTBEMdB7QerocbOvSsq8NuQU2DGx9troGsKKbVtDQ/u242AKCh1YdBZXldPMOeY8yaWeweQERElASx+ohqnrj95G4FtpnmtFv0Jv3RaJOcXI7I5zJyUEHM+2kBqsOmZk6BzslhWpusaH1s7VZRLxXY+nWDnrEtK3TAZrOgtrEDdptFzxDPnjSwy+eYqPAFESgzmGklIiJKgvB4S1upySIKuPi0schz2vrEuvUuhxUdoX6n0Xj96m3RZtXbrBbccemxUe+nBarGYFf7fazbUQtJlqOWT9htFowLlSS0tPv14NdqFVFe7FQf1yLCbhVhtQiYOSH5vVS1kDXOYl+UBtn/6iEiIuoD5LCoVZIVyLICSVYiWkNlM5fDCp9fgiwrCAQlSLKMVVs6e82u2nIYLocVi04dE/X+U8aUR71e6xCQZwh2tQD0s+1H8dn2o3rG1chus+DuK2YAAPxBGdZQoOvxBTFmiBrM2qwirFYRU8eUm/afNHqilVFrJrE8gIiIqJdkWYlofi/LCoJKaAZ8EvuGplpeqA7V4w/i1kc/xuRRpdi2t0m/XZIV/OZHpyS832iZVqthla43V+3F2bOHR9zPbhVhEUW4HFZ8sOkQDtWpta4/unQ6pk8aiIkjilHgsuHS06owYmDs8oTeYKY1OzBoJSIi6qXw2e/qdQoaWrwAkJIZ7amiTZ7yeNUyAGPACgBXnDm+R/vVgtY8R2cm1LhK15HGDjS0eiPu5wh1GAhKsh6wAkDVsGLYrBZMG1uBYFDG3CmDejSu7pg/cxjqWrw4ZlTsSWiUegxaiYiIeikY5bT21zWtetsmm63vBK3OUCY0vK61tNCBmeMH4LjxXdeMRptwppUCGDOt4ROc/vnpPv3nEZUF2H+0Xe/9monVxDT5Thuu/eakjD0+qRi0EhER9VK0We/akqVAHy0PCAtajx1bjisWdC/L+uitJ0Vcp7W8coStzKUuOhD5+/vRZdNRfbClW49HuaHvfPUjIiLKUl0tGmDvQ5lW7TS+L2BuexWtd2ssDpslIjjVMq3hAfxTd52OhSeNDt0m4vL5VShw2VCcb09JJwDqu5hpJSIi6qVos97//dkB/WdbH8q0anWmjy7/Iqn71Wb9RyuVKC1UFyUYVJaHs2aPwFmzR0RsM3FECZx2KzZV1yd1XNR3MGglIiLqpWCUiVj7jrTpP9ssfac5fXgf/cHleTjc0NHrbk9aBjfapDRthayyImfM+999xXEAgL9//DXGDS/p3WCoT+o75yuIiIiyVLRMq5HV0nc+brWJT5ozZ6ltqHrb7Umr+7VFDVrVHJqWcY3nwpPHYDJn8eekvvMqypD1O46ivtmT6WEQEVEWi1bTOtMwy94i9p1MqxiWai3rRiDZHVo2VWupZeQP1c92J2il3MWgtQtP/n0rHvrThkwPg4iIsli07gHGxQYsfSjTGl4eoAWZvW2sf8yoUlz7zUk4edqQiNsmjixF1bBinDRtcO8ehPq1vvMqyiCPT+p6o15SFAW/fGUjXlrxVcofi4iIkitaeYCxjVOfyrSGjTVZYxcEASdNGxy1PKDAZcO9352JkgJmWik2Bq1xHG5QV94IfwGngqIAX+5twvsbDqX8sYiIKLmirYgVCHYmPPpU0BqWarXok8i4hillFrsHxPHMP78EALR7Ail/LONppL9//DUK8+zId1oxZ3LqlqUjIqLkCEYpDzBe15cmYhlj1rOOH64HsQxZKdMYtMbR1pH6YFWjGILWN1bt1X9m0EpElP2ilgcYlh1Nxxm7ZDFmWhXFkCVm1EoZ1ne++mVA+CmSVIpyZomIiJJIVhT86d2daGjxJn3f0coDulolK1sZA+xtexv1y4xZKdMYtMZRlG8HAMybmvpsp9zbaZlERBTXn/6zE++uP4g/pmDCqxwqBTjvxJH6dYEuerdmK2O+xmET+1TnA+rf+JcYh9bCpDg/9bMZlRhB61f7m1L+2ERE/Z3XH9Qnumo9QZNBURR0eAP658U5J4zE/940FwAg9dVMqyFqddgseqAQ63OKKF0YtMahveGk44UapYYfANDQmvzTWEREueZNw1yBZNaXrtx4CD949GM0t/kAqPWf2v6j9W7tCwRD0Gq3WTI4EiIzBq1xaG846fhyGV4eUOCyATC/eRARUc94DdnVZM7k37irHgBwuLEDTrsFNqvYGbT20UyrkUUUAG0eVt+MwakfYdAah9auJB31pkrosW751hRcceY4/HzxCQD6Vm8/IqJsJSWp0b+iKNi6u16/3OENAgDqmz0oK3JCEPp+ptXoijPHQwA/hyg7MGiNw9gYOtW09zab1YIzZw3XM60+f/rGQETUXxln9/dmYtHnX9XhnidX4YtQ4NrhU4PWumYvyorU+Q9aUByUFYweXIjHbz+5x4+XaeXFThQX2DG4PA/nzBmR6eFQjmPQGoe2fGs6Mq1bv24AAGgJAFEUYLeKplNaRETUM2MGF+k/Wy09zxw2t6u1q21utY+3x6v+X9fiQXmRE0DnRCZZVmC1iMh32nr8eNnAahHxwPVzMGpQUdcbE6UQFxeIQVEUeP3B0M+pf7zn/7UDAOA1ZFYddgszrURESWA1rHdvt/Z8cpGexAjFvVqmVVGA0kI109pZ06r02RPr1593DA7WtWd6GEQmDFpj8AfkzmA1jWVJR5s9+s9tHQH87aOvcd6Jo9I3ACKifshYX2q39fwkox6z6tnUztsK89Te3lp5gKwo5qanfcjcKVyNkbIPywNi8ISyrAAgpzFqLQ4taEBERMmjnqoXMGxAARQZONzgxrXL3kdtY0dC+9GC1mhzubSyA2Of074ZshJlJwatMRxtUjOegpCe8oDZkyoB8NstEVEqSJICURRgEQVIioLt+9SFW6oPtSS0H61vt5ZpNSZStVZaxuv6aKKVKCslHLSuXr0al1xyCY477jjMmzcPS5cuhderNsC/7777MGXKFMyYMUP/9+qrr+r3ff3117FgwQJMnz4dixYtwsaNG5P3TJLs65pWuBxWDK8sSMviAoGgjGljy03f0DVc4pWIqHckWYFFFCGKatZVa4FlSXBSVmd5gPq/seerlnwQBEEvEWCvbaLkSShobWxsxI033ohvf/vbWL9+PV5//XV89tlneOqppwAAW7ZswdKlS7Fx40b932WXXQYAWLt2LZYuXYply5Zh3bp1uOCCC3DzzTfD4/HEe8iMmTlhAG751hRYRDEtmdaAJMMWow0LJ2MREfWOJMuwiAIcNgt8AUmvcbWIieVutCA3EFCLWZ12dVLX0AH5pn0xWCVKvoRerWVlZfj000+xaNEiCIKA5uZm+Hw+lJWVwe/3Y+fOnZgyZUrU+y5fvhznnnsuZs6cCZvNhquvvhqlpaV4++23k/JEkm1AiQvHjCqDKKjfylMtGJRhs5oPx6WnVwEwdxQAgK17GtDW4U/5mIiI+gtJUmCxCCjKt6Ol3af3bU30TJp2NqwuNGlWC2Kv/eYk03admdZeDZuIDBLuHlBQUAAAOPXUU1FbW4tZs2Zh0aJF2LFjB4LBIB577DF8/vnnKCwsxEUXXYTFixdDFEVUV1fjoosuMu2rqqoKO3bs6PZji4Y1nZNFazIdq9l0RYkLR5o6TO1SUiEoK7DZRNPjTBhRAgDwBSX9eo8viEde3YwTpwzCTRdG/4LQV3V1LCh9MnUsUv0666v42ug9BYBVFFFa5MSBo+369FpJVhL6u9PKtepaPLBaRciygm+dMgbjhpeYttOCVlEQ+HedInxdZI90HYset7xasWIFWlpacOedd+K2227DNddcg9mzZ+PKK6/EI488gu3bt+OWW26BKIpYvHgx3G43XC6XaR9OpxMdHd2fuVlWlp+yUy5FRa6o18+YOBBP/30LXPkOOO2p6xAmK0BBvgOlpfn6dSNCrVQkCPr17bVtAABvQDZt25/EOhaUfuk+Fv31bzpZ+NroOZvdCptNxOCKAnyyuQaWUK9Wm92a0N+ddr+9R9rx02fWorndj/w8e8Q+tAyszWbh33WK8XWRPVJ9LHochTmdTjidTtx111245JJL8PDDD+PFF1/Ub582bRquuuoqvP3221i8eDFcLpc+YUvj9XpRWlra7cdsbHSnJNNaVORCa6sHkiRH3F5RaIckK7jknrfw5H+dqi+vmmxeXxByUEJTk1u/TpDVsoADh1vg8wbw8z+sxwXzRqnjFmDatj/o6lhQ+mTqWPS3v+lk4Wuj99wdPggArALg9gbR0KQmTJpaPAn93bW71RWxDoQSCADg8wUj9qElWIJBmX/XKcLXRfYIPxap+qKWUNC6YcMG3HvvvXjjjTdgt6v9RP1+P2w2G1atWoXW1lZcfvnl+vZ+vx9Op7qs3bhx47Br1y7T/qqrq3HKKad0+/FlWUlZfakkyQgGI//ojTHy0cYOOAcWpuTxA0EJFlE0jUEMdfj715r9OOXYIQCAN1btBaA2x4423v4g1rGg9Ev3seBxj4+vjZ75y8pqbNvTCFEU9BrTdo+6/KrXLyX0O/UHom2rROzD+NnBY5ZafF1kj1Qfi4SKDyZMmACv14uHH34Yfr8fhw4dwkMPPYSLL74YNpsNDz74IFavXg1FUbBx40a8+OKLeveAiy++GG+++SbWrFmDQCCAF154AQ0NDViwYEFKnliyGNuZdHiDcbbsnUBQjrke9oGj7QiE/RH0ZhlCIqJc0dbhxztr9+PA0XZYxM5WVO7Q+3ldswfX/+9KHOnmIgPBKBm9MYOLIq4TORGLKOkSyrTm5+fjmWeewS9+8QvMmzcPhYWFOP/883HLLbfAbrfjnnvuwf3334/a2lpUVFTg1ltvxcKFCwEAc+fOxX333affXlVVhaeffholJSWpeF5JY2xDJaWo91Wr24/mdj9aOwIRt805ZiCa2nwIhL1Rhl8mIqJIxrNzFlHQZ/93eNX32y/3NkKSFWzcWYdz5ozscn/hQeuS7xyH8WGTsABE7blNRL2TcE1rVVUVnnvuuai3XX755abygHALFy7Ug9i+wphpTVVpwj9W7QEA7DrYHHGb3WZBa4cfG76qM10fnnklIqJIxrdtiyhGZFr10/3djDHD33vLihxRt9NbXiUwViKKj30iumBsVSKlKGgtylPrg+/5znERtzlsFhxu6MA+Q9E/AKz9sjYlYyEi6k9ME3SEztP22lLdWm1rdwUlxdRTW3v/DidyRSyipGPQ2gVjnWmqMq0+v4SBZXnIc0Z2JujwxX5DbWrzpWQ8RET9xabqev3nlnZfrzvQBCUZDps6p2D2pErYbdHnFyS70w0RMWjtUjrKA/xBCfYYzaf3Hu7MsFYUO/GtU8Zg2U1zAQA19WyjQkQUz18/3K3/XNfsxZGG6BOuJEmBoijYtKs+7qTboCTrS7fGWwLWInAiFlGyMWjtgnEi1sG6dly77H20uJO3hKqiKPD4JNht0Q/FWccP138eWJaH808cBWfom/3Dr27C3z76OmljISLqb6qGFus/DyrL01e00hTnq6f3vX4Jm6rr8dhrX+D3b2yLub+gJMMWeg+O1fEFAARmWomSjkFrF4yneD7bfhQA8HVNS9L2v3zlbqzediRmC6uTjx2CWy+aCqCz158xwF299XDSxkJE1N9IUmeQeu03J2HKmHL98g8WTcWvbj0JwwYUYP/RNjz+2hYAaoIimg5vAJurG3A4dJYr3pKV+46oZ8nYRYAoeVK3Lmk/pL31yUmcuP/vdfsBQK+Rika7za8FrYYAtyg/+sxVIiLqnEB717dnoGqYmnV9bsl80zZOhwUHj3YGqrG6s7y/4RAA4PSZw7Dy84N6h4C4GLMSJQ0zrd3w7H+frv4QOq2kJLFfq7YrW4yaVqAzaNXeSI3Z33wXv3cQEcUiyTJOOXYIJo2MvWR49cEWNLd3ln3FCkab2nwYMbAAV5w9EUD0RQXCMWYlSh5GPN0gCILpTSy8JioZ4rVd0YPWKAsKbP26EYcb3Bhcnpp1fomI+jJJUmCJU3saTayZ/wFJhs0qYlB5Ph697aSY7a5MWB5AlDTMtHaTJCuoDfX1k2UF//PCuqT2St2+rynmbfbQTNVY6/mu3tY5jqAk49+f7YeUzBoGIqI+SpKV7p3GN3A5oudzJEnWO8qUFTm7t7MUraRIlIsYtPbAPz7Zg31H2vDSiq96tR9jmUFRXmSPVk28TCsAjKgs0H/+eHMNXn2/Gl9UN/RqbERE/UFQVmCN05oKAP7n2tn6z3MmD4w5eWr1tlp8tb85ocdnzEqUPAxae0DLuPb2zci4wlZBnNNMzrCa1nj72XVQ7WwQq+E1EVEukSS5y/KA4ZUFuOjUMRhakY8Cpy2p8xZSUU5GlKsYtPZCb9+MtFYsJQV2XPWNCTG3s4VaXBnfSH923Ww9O2AsBdi6p7FXYyIi6k+6Wx5w7txRWLr4BIiiEPe9/YRjBib0+NY4bbGIKDF8NfWCogBLfrcar/ewwb8WbF5x5niMG1YSczvtVJWxhmrYgAIMqcgL7Ud9g21s9eoTuh5+dRN2H0peP1kior4o0ZpWf0DCYcOqWb6ABJ9fAgDkO60YNagwocfv1mQtIuoWBq29oCgKjjZ78Oane3t0/2Ao09qdN9SbFk7GHZcea7pOC2a1oFUrW9A88MfPsX0vM69ElLvU8oDuf9R9sKkGAOD1q0u53vmbVfjBox8BAHwBOeHSq8L82PMViCgxDFq76UeXHgun3WLqXuI31Jhqb3CJ0ILN7ryhzp40MGK2qtaKSysziBb7Hgqt3EJElIuCPegeAHTOWXB7g5BkBbKiICjJsMfpqR0NM61EycOgtZumjinHk3ecihsvmBz1dm/o9FEipFA3gER7CBpZLIK+ny/3RrbNKnDxWz4R5S5J6mnQaq5rDQS0ZbQTzLQyaCVKGgatCYq13KqvB0FrMJRptfbgDVVjFUU9YxutTKEnwTQRUX8hyYmVB5w2fQgAQA6bi+X2qvMF7LbEPjYrirvZz5WIusSgNUGxgtbeZVp7fhisFgFHmz1oafdFvd3jS7xsgYioP5AVBYrSvXkDmqljywEA/1l3ADc9/IF+/Z1PfgoAKC1MLAgdmeDELSKKjcu4JijWqaGe1LRqE7GsvSoPEPHhphp8GJo8AAAOu0XP/HYwaCWiHCUlMNlVo01wjTXBdvRgBqFEmcJMa4IcoVNDoiDgtounobLUBQCmtldNbT4crGvHwbp2+AOxM7D6RKwuVmuJJ7wsYdEpY/CDb03FpJGlGDaggJlWIspZWlvBROYNiGEBbnjAK8RYLYuIUo+Z1gRp5QF5TiumV1Vg2thyfP/hD1HX4tW3uffpNXowOagsD7+4YY5pH0ebPagscSEYKg/oTaY1PJPa1hHA5NFlmDy6DMte+pxBKxHlLEmfN9D9xED4Eq52mwiPT30//+X3T+z2fu797kzUNLB7C1EyMWhNkFYekO9Uf3WiIGDB8cOx9stafRtj9vNIY4fp/h9vrsHz/9qBb5wwAu+s3Q8gsVNXXSnM6+wW4HJY9TdbIqJc07PyAPNlf6hrwIlTBkW0HYynalgxqoYVd3t7IuoaywMSpGVa8w2tpAQh9rJ/syYMMF3+fGcdAOgBK5DclihDB+TrP7ucVta0ElHO6uyF3fPyAElWMHfyIFx9zsSkjo2IEsdMa4LsNhGnTR+CM2cN168Thc5G1OEUAE/+fSscNhHXnXsMWtr9pttHDCyAy5G8wzB2SOc3ezXTytNTRJSb9A4tCZQHRKtZnTd1EKy96PJCRMnBoDVBgiDge98wf+MWBQFyeFO/kEBQxhe7GwAA1517TMS3+LIE26fE8rNrZyPPaUVRfmfWNs9hZU0rEeWsQA/mDRTnR575GjuUp/mJsgGD1iQQxNjlAeHdA8K/xFsTXBIwlmGVBRHXuRxWdHgZtBJRbtLaCtqs3V/FamBZXsR1sfpzE1F6MWhNAlFAzEyrPyibLwfMl2296BzQFZfDCo8/CEVR2KaFiHJOINi7Di1LvnOcPumWiDKPr8YkEEUhYsk/TXimVTtdpZk6prxXjz1zwgD9jTlcnsMKRVFX60pm3SwRUV+gtRW0JXhG60eXHougJGP88JIUjIqIeoqRTBIIEKCEygPCywSMy7vKsoJgsPPyb//r1F6fdrrlW1Nj3qYFqh5fkEErEeUc7Qt9okFrb5MJRJQajGSSQDTUtGp9ATXGmtLF/7vSdFuq66TyDEErEVGu0YNWzvwn6hf4Sk4CtaZV/VlbNlATrU/qqdOHYNmNcyKuTzaXQw2Kf/rsZ9hf25byxyMiyiY9LQ8gouzEV3ISiKJaHvDl3kbsqWnVrw9fWEAzvLIAlaWRM1STzVgScP/z61L+eERE2aRzIhY/6oj6A5YHJIEoCpBkBb98ZZPp+uICR9Tt03WqinWsRJTL9D6tzLQS9Qt8JSdBgdMW9fqSgujLs7Z5Aqkcjs5pN9fMhpcuEBH1Z4GgDKtFgMiWf0T9AoPWJCiKsoIKABTnR8+05qUpAxremzVWaywiov5IDVr5MUfUX/DVnASxgtZomdYHb5yDU6YPSfWQdNedO0n/mUErEeWSgCRzEhZRP8JXcxJUlrqiZk+jBbMDS/PSeqrK+FCBoIymNh9eeW8XSwWIqN8LBhm0EvUnnKmTBKIgoLTIgY46c3urPIcVLocFHp+Ea745MSO9Ao0BciAo456n1gAAJo8uYwNtIurXgpIMq8iglai/YNCaJD6/ebnWc04YgYoSFwA1aDxp6uCIGtN0MD6m31AesOdwK4NWIuqX1u84itc+3I1jqyogipyERdRf8CtoisybOhgAUFniAhA5KSoTjAsM/P3jPRFLzhIR9Qd/++hr1DZ5EJRkWBi0EvUbDFpTRAsHf3Tpsbjr2zMyNo7GNq/+87NvbTfd9ru/b033cIiIUk5bDbCtI5AVCQMiSg4GrSmivU0W5dsxaWRpxsYhSZHZ1DFDigAA67+qS/dwiIhSzmlXK9/qmj1QeEaJqN9g0Jok4V/mh1TkZ2YgYaKVABwzSg2iRw4sTPdwiIhSTltYZe+RNhyqd2d4NESULAxak0RAdp6C0mLWGeMqAAAOmwVnzhoOABg9mEErEfU/XMKaqH/iKzsF8p3Z82uVZTVq1frILjh+GIry7Bg9uIgTsYio3/jDOzvw4aYazBhXgZKC6KsRElHflj3RVR8nhGao/vL7J6KsyJnh0XTSAlNfQG3JVVGsdjMQRYDrCxBRf/HhphoAwMZd9RkeCRGlCoPWJLFZ1KA123oCautuz508CBAEHD+xEoC66MAnWw4DAK41LPVKRERElI0YtCaJJbTqSjqXaO2Ob5wwAg6bBceOq8CM8QP062ubPACAT7YcZtBKREREWY8TsZLk5GPVxQQK8mwZHomZw2bBN04YERFMt7r9GRoREVHqFbhsGFDixNAs6eRCRL3HTGuSzD9uGE6fMZSNrImIskC7J4DHfnhypodBREnETGsS9cWAtTjfnukhEBEREXWJQWuOG15ZkOkhEBH1miVsEuzPrp2doZEQUaowaM1RJ01Ta3Almb1aiajvC38vG8Yv5ET9Dmtac9S135wEf0DCkYaOTA+FiKhXFC6UQpQTGLTmsM+2H830EIiIek1bPIWI+jeWBxARUZ/W4Q2aLt/17RkZGgkRpRKD1hx26elVcDksmR4GEVGvhAetk0aWZmgkRJRKDFpzmCgK4DwsIurr3N5ApodARGnAoDWHCQKgMGoloj6uwxfseiMi6vM4ESuHiYIAmbNuiaiP08oDvjlnJI4ZxdIAov6KQWsOE0UBspzpURAR9Y7Wo/WiU8f0yZUJiah7WB6Qw0QBzLQSUZ8nywoE9M2ltImo+xi05jAx9AbPwJWI+jJZUSCKDFiJ+jsGrTlMy0rInIxFRH2YLCvMshLlAAatOUwMHX0mWomoL5OVzvczIuq/+DLPYSwPIKL+QJYV/f2MiPovBq05TKsB+2p/Ez7cdCjDoyEi6hlFYdBKlAvY8iqHaW/yjy7/AgBw6vShmRwOEVGPcCIWUW5gpjWHceICEfUHanlApkdBRKnGoDWH8U2eiPqD1o4A2jyBTA+DiFKM5QE5TGDUSkR9XLsngPc+P5jpYRBRGiScaV29ejUuueQSHHfccZg3bx6WLl0Kr9cLANi8eTMuueQSzJgxA/Pnz8fy5ctN93399dexYMECTJ8+HYsWLcLGjRuT8yyoRzhxgYj6uiONHZkeAhGlSUJBa2NjI2688UZ8+9vfxvr16/H666/js88+w1NPPYWWlhbccMMNuPDCC7Fu3To88MADePDBB/HFF+okn7Vr12Lp0qVYtmwZ1q1bhwsuuAA333wzPB5PSp4YdY19DYmor/P5JQDA/948N8MjIaJUSyhsKSsrw6effopFixZBEAQ0NzfD5/OhrKwMK1asQElJCb7zne/AarVi7ty5OP/88/Hyyy8DAJYvX45zzz0XM2fOhM1mw9VXX43S0lK8/fbbKXli1DVmWomor/OGglanndVuRP1dwq/ygoICAMCpp56K2tpazJo1C4sWLcKjjz6K8ePHm7atqqrCX//6VwBAdXU1Lrrooojbd+zY0e3HFkUh6W1NLBbR9H8usVnNz9lqzezvIJePRbbJ1LHI9N9gtuJrI7a1248AAPJdtrT8/fBYZA8ei+yRrmPR46+mK1asQEtLC+68807cdtttGDhwIFwul2kbp9OJjg613sjtdse9vTvKyvJT1qapqMjV9Ub9TFGjuTSjtDQ/QyMxy8Vjka3SfSyy5W8wW/G1YdbY6sX6HXUAgAEVBWlt48djkT14LLJHqo9Fj4NWp9MJp9OJu+66C5dccgmuvPJKtLW1mbbxer3Iz1c/hFwulz5hy3h7aWlptx+zsdGdkkxrUZELra0eSJKc1H1nO7fbZ7rc1OTO0EhUuXwssk2mjkWm/wazFV8b0W346qj+c3NzeiZk8VhkDx6L7BF+LFKVgEgoaN2wYQPuvfdevPHGG7Db7QAAv98Pm82GqqoqrFq1yrR9dXU1xo0bBwAYN24cdu3aFXH7Kaec0u3Hl2UFsqwkMuRukyQZwWBu/dErYb/Lt1fvw5xjBqIo356hEaly8Vhkq3QfCx73+PjaMDvSoAaqd14+Pe2/Fx6L7MFjkT1SfSwSKj6YMGECvF4vHn74Yfj9fhw6dAgPPfQQLr74Ypx99tmor6/HCy+8gEAggDVr1uDNN9/U61gvvvhivPnmm1izZg0CgQBeeOEFNDQ0YMGCBSl5YtS18Kz1K+/twu2Pf5Kh0RARJeaz7Wqm9ZhRZRkeCRGlQ0KZ1vz8fDzzzDP4xS9+gXnz5qGwsBDnn38+brnlFtjtdjz33HN44IEH8Nhjj6GsrAw/+clPMGfOHADA3Llzcd999+H+++9HbW0tqqqq8PTTT6OkpCQVz4u6gd0DiKgvGzmoEE1t3q43JKJ+IeGa1qqqKjz33HNRb5s6dSpeeeWVmPdduHAhFi5cmOhDUopoMavNKiLAUytE1MdIkoyyImemh0FEacLGdjlMy7RaLZ1Ba1mRI5NDohxz7bL3Mz0E6sOCkgwr2x0R5Qy+2nOYEKppNc66ZMkApYuspGZSJeWOoKTAauF7FlGuYNCaw7R5WEFJQYHLhpkTBqDDG8zsoChnpKoTCOUOZlqJcgtf7TlM6x4gKwqmjinD2CHF6PAFcbiBvTIp9RRmWinE4wvC40v8C3OHN4g8B6vciHIFg9YcZiwFEAQBh+rbAQAfbqrJ1JAoh8ic+0chP3zsE/zg0Y8Svp/bG0S+05aCERFRNmLQmsOM5auiIGD8sBIAQEUxZ+NS6kksD6CQoCSjJ4l3tzeAfBczrUS5gkFrDjNmWkUROHZcBQCgnC1kKA2CUZZdXLXlMGtdqdvc3gAzrUQ5hEFrDjOuiBWUFFi1bgIMGigN3vlsf8R1z761HXf8ZlWUrYnMAkEJ/oCMPCczrUS5gkFrDjNmWj/desQ0MYso1VrafVGvb3X79Z+3723EI3/ZlKYRUV+idTphppUodzBozWHGTCsAWJhppTSK9Xc2vaoC2/c1QVEUvPSfndj6dSN8finNo6N0SbQc5HCDG3/7aDd8oQVR7DZ+jBHlCp5XyWHh6wiI+mIDDFop9WIFrZuq67Gpuh5XnzMRtlAPznZPAA67JZ3DoySTZQV/XPEVzj9xlGnp1WZDxr2tw4/CPHvc/fz53V3YuqcRn39VBwCwW/l3QZQr+BU1h4WvI6OVC7A8gNJhUFle3NsPN7ihxbVN7T788d9fob7Fk4aRUSocaezAh5tq8PrHX5uur2vuPKYff3FY/1ntKBD5XpTvUssBDjd0AABsVn6MEeUKvtpzWmfY+q2TR0MQBIiCwPIASgtXF03hV248BED9W9xcXY+VGw/hoZc3pmFkQH2LB0/+fSsCQZYlJIvWLcK4gtXaL2vx0J/UYzp+eAmqD7YAUL843/B/H+CNVXsj9lPoMtewFuXHz8wSUf/BoDWHGcsDxg4tBqCWCLDlEKWDPyChKC/2JBp/QEZHaJWk2iY1G1cYZ/tkevX9aqzfcRS1jczsJov2Zdgqqh87+2vb8Ps3tum3lxc50OENAOjMom7f1xSxn3xD0HrPd49DaaEjZWMmouzCoDWHGYNWLfthEZlppfTwB2S4wmZ+a5MBZ00YAAD6BKz1O44CAOxpOhV84Ki6OlwgSi9Z6plAaOKUxaIe479/vAcA8OitJ+HhW+Yh32mDO/QlpaZeXUp6cHlkCYmxZKC0gAErUS5h0JrDBEN5gFYXpgat/KCm1PMHJditIn75/RP16xafdwwevmUeTj9uGADAFzD/Le482ILWDr/punZPQA+IkqWxVZ0ctGZbbVL3m8t8AfULSGObD4qioDDPhopiJ4ry7SgtdCDfZYPbo2Zaf/v3rQAAh82Cf63Zh901Lfp+jF+qu5q0RUT9C4PWXGbItGqztFkeQOniD8iw20QUGE732qwiSgsdehujaKtmvfreLtPl2379MR577Yukji10Bhv/WX8g6hgocV5D1vzWRz/Gmi9rUVnq0m/Pc1rh9gaxw1AS4A/KWP7BbvzfnztrmSVJQWWpC88tmc+OEkQ5hkFrDjN2DzBnWhm0UuqpmVaLfrrYyBjIXnTqGNNt4dlXANi2pzGpY5MkBdPGlgMA2joCSd13rtq2p0H/+ewTRuDcOSNx4cmdx7bAaUMgKON/DQFqU6sXgPmsUF2zh0tNE+UoBq05LFpNKzOtlC7+gAybVTStzHawTq0lLTNMrjGueDR+eAkchmbyb63em/Rx7TzQDElWUBQ69axNDtIcbnDjib9tYRlNAqoPtuCjzZ3trM4/cRQuOGk0qkITQAEg3xXZTeJA6O/BacioHqx3Y9iAghSOloiyFYPWnBarppVBK6VWhzeATdX1aGrzQTAErcdPrAQA2KwWnHLsEACA09EZsIgCYPzzfO1Dc8/PZFj28gYAQEGoU4HWwUCzfOVubNhZh1Y3M7Dd9cXXDV1uE74c68BSl15brB0Lf0DC0aYODB2Qn/xBElHWY9Caw2JlWiVJwfa9jTjc4M7QyKi/23OkDUDnLH0AqCxxYXB5ZzAyYXgJAMAiilh83iRc+81JEATBNHs8ld0EtPZan20/arpeW3zD6w9G3IeiE4AuW1Plh/VfHV7ZmU3t8Kq/68MNHVAUMGglylEMWglAZ6bVZhVR1+LB/72yCT9+em2GR0X9lRQ2uenCk0bj1ounma47bsIAXD6/CtOrKnDilME4adrgiExrKifiaOUB731+0HS9Vj6jBVLdce2y93Hrox8lb3B9jNcvmU7xR5Pv7CwPePru03BsVYV+udXtx4Gj7fjbR19DFAQMKWfQSpSL4i9JQ/2asZbQGpoME5QUfU1volTRZpJ/+8xxAIALThodsY3DZsFZs0eYrgvPtKZyxWFFAS6YNwpvrNqLmno3RFHAf9Yf0Mtn3N0IWmVFwW9f36pv3+r25+QKTkebOlBR7NIXDYjGae/8OLKIIk6cMgh5Dis6fEE8+9Z23PfcZwCAGeMqulxNjYj6J2Zac5mhPECrK9T6JGqa2nzd2pUsK5yYQt2mBa1nhPqxdpcgJHeiYH2zB/5A51KttU2dQVVQknHilEEA1NfBvU+twcoNh+APLe3a4u76tdHS7sfnOzu/BN7++CfJGnqfcrCuHcMq42dHrWFdJARBwIzxA1BRbO4UcPykyqSPj4j6BgatOSyy0ZBa02r0X79Z1a193fXbT1lOQN3m80uw28SIv7euCEJndjUQlNHu6flkKEVRcPfvVuO5t7erYwpIuOf3a/Tb504ZBGcoo3fUEMzuPtQKAKhv9vbocR9+dVPO1cM2tflR0UWbKuOEPKPwBQSOGzcgaeMior6FQWsOi/YhEZ7t6K6mNh+ONnnw7Ftf9nZYlAO8AQkOW+L1qKKhPMA4iUubtJUIrSvA7kPqakt1zR79tktOHwuHzaIvuuE1ZGM1Kzce6vLsQrTbt+1pxHZDA/1E7DvS1uda0smyAllRYO3GpLkFs4bj5gunmK4zllPMnlQJew/+boiof2DQSiZWsXd/Equ2HEnSSKg/kyRZ71iRCEEAtJBt2151QYFpY8sR7EFpSkOLmil1hGopm9s7T/dPHFEKoHOCYrRJV+2eAK7/3w/w5qd7Yz6GJHUGmDMndGYIE5nEpdmxtxE/fWYtVm093PXGWURbUaw7x/vbZ47T255p8gwTtPxRFpYgotzBoJVMoq1ORJRssqLAkmBpAKBmWrWWU69/pPZoLStyIhhMPPuo9QCtqVdbuz3y6mb9thED1XZLFlFdiynepKu31+yLeZtxCdhjx3bOhu9J0Lpldz0AwNOD+2ZKQ4sXL/77KwDdC1qjEQUBJ08bDAB6PTER5SYGrWQS/sEyZUxZhkZC/ZkkK6buFd0lCIASdnrcKgqm4LC7OnzR62Gv+sYEWEJnHARBgM0qmiYo/vSqWfj9nafpS826YrRyavcE8Mhf1ED4+vOPwdwpA/Xb/vzeLjz7zy8Tqsn9KlRSsGFXPb7Y3XWz/nTauqcBH2w8FHH9n9/bhU+3qmdfrD34kqK5/Ay1y0QgyEwrUS5j0EomWk3rzRdOwahBhdj6dSP+8n513PvIqew7RP2SLCsJT8ICQssMK531p2fMHAarVexR0GoMgIzB46nTh5q2s1pE01KuowcXqYFs6LpoLaz8AQm3/fpjvfvG8RMr9UBYs2rrEdz264+7NdY1245g7TY1+Nt5oBmPLt8MX5Q620x55NXNePHfX2F/bZvpemN7MptVRElBz9p9af14jQsOEFHuYbM7MtE+WIdXFuhtid75bD8unV8V8z4+f/Z8eFLfIMk9Kw/wB2TUNnXgv3+3GgAworIAdS3ehILWpjYf1n5ZayqFeeyvXwCIvliBGqBGnpLX4rFDdZErx/1zdWfJwMQRJRFnMM46fjhWrDsAQO1aYLUIeOOTvSgvdqKi2InRg4tMvUifD3U4MGpu82FgWV68p5p2jW0+jBhYqF/WfkdXnDkO44eX4I5Lp8PXg1P8oiDgFzfMiWh/RUS5hUErmWiZVkEwz6aOxxO2NrvbG4hYR5zISJEj26t1x6bqetPl8cNL0NRei4DU/Wz/s299iS/3mmfvV4c6CCy54riI7VvcfrS4/RHXDyzLQ21jh77YAKCedXjqjW042tT52rnz2zP0n6dXVaC2qQMzxlXoQWtjqxcdvqBpQldlqQvLbpyrX8532nDeSWOwYcdRvdtBNmVa851WuL1B7D3ciumGlawaW704bcZQnDlrOABgWC8ypYOyLEAnovRjeQCZWEIZIVEQTB/G8TJZq7aos5m1FkbLV8YvJyCSlJ7VtGomjijB7EmVGFiWB5tFjFgWNp7wL1nGYGjkoMLwzU2eWzJf//mmCybrP2slMp9uOYLPth/F3iOdp8mNz/PWi6bigevnYMKIUr2104+fXhsxJmPQC6iLMbgcVtx9xQws+c5x+nXZYHdNi56JfmPVXjS1+eDxBeELSGhs86Gs0JHhERJRf8GglUy0yRLhAUWsD0hFUfD6x3vUn0PNiLLlw5SylyzLPcq0XjBvFERBQIcviLxQNt9iEREIyqb6yXiChqzsT6+apU+omjSyNOr2Y4cUAYisXR05qBDfDwWe3lDQ+VyU0/hGxt7IU0Z3TnL8ck/svq1HGjvQ7glg6IACuBxWDC5Xg+x9YfWjmfKfUMZY87cPd+Px177AzQ9/iHZPAPkunnUhouRg0EomWu2dIAAXnToGwwaop/PCM0GaaAEq1wWnrsgyelTT6nJYISsK9te2Iy/0d2azCPAHZbzaxYRBAKg+2GJalMBYOxprPNeeOwmA2tg+XH6oh2i7Nxg1aL73uzPjPhfNO5/tBwD89xUz8L2zJ0BAZ/Z206562G0iZk5Suw9oQfaf390VdZGC+hYPJFnGjn1NuHbZ+3jv84Mxx5AMUlhpxqF6N3bsb9Yv87Q+ESULg1Yy0SanyLKCc+eOwpVnjwcA+GO0mmnriKz1Y9BK8azccBCfbDmsZ+YTYczO2m3q25dW0rJi3QHsOxI/+/jvdfsjrnOGJl/FCloHluXhe2dPwPknjoq4rSR06ruh2RPxBW7MkCJUDSuOO55Hbz1J//mkaYMxYUQp8pxWKAAaQ4sf1DS4MbSiQC+/MWZraw3LywJq/9e7f7sa9z61Rg+EX/7PTlP3g2Rr6fBj7uRB+OX3T8S0seV6acR9Vx+PJ24/JWYGm4goUQxayUTrHhAM1bNqZQLhvTE1bcY+k4q2Dy5QQLH9ccVOAMDuQ60J39dYtqJN9jMua7rmy/grshnbXC0+T82gah0DYpUriIKA02YMRWFeZLumylIXrBYRB+vcaDVM1rry7Am49puTuno6KMq36xOXrjhT7UVaGgqE7316LQC1QX9FiXnWfFFeqDRCFFBT78b6HUfxyKubUN+i1sLWNXtN4zncYA5uk6nV7Udxvh1lRU6MDHUOKC9yYuSgQtNqVkREvcV3FDJZdMoYKIqCAaEPSe2DPFYv1raOzqD1tBlDsWLdAdMErlT4eHMNnv/XDtOkGMoNWoA6enARTp0+BEBkL9Bomtp8+PiLGn1CYdWwYpw4RV1lyWmLH7TGYxFFDCpz4UhTB0a61YDtlm9NNS3Z2pVbFk1BQ6sPztByslVD1eys1t6prtmDUYPNE8TmTB6EFesOoL0jgJ88s1a/3ridcTJYTYMbY4fGz/r2VKvbr9f7lofGXFbEyVdElHzMtJJ+mhVQP3RuuGCynnHVMluxAlFjrevlZ4zD4PI8HKxrj7ptsvz9E3XiFxc16Ht6e8yCshp0fuOEEVGXBY31d/rcW1/i7x/v0RcRcBr6sWrB6udf1fVoTE67FX6/hI821wAAJo4sSej+FlFEZYlLvywIAo6fWInSQgfqmj2ob/Fi9OAi033OC5UqLP9gt+n6g0fNPWPnTRmEylIXduxrTmhM3eUPSPD6JRTlq5lfLVjt6ZKtRETx8J2F4rYe6irTqmWuZo5XM0seXxA9KFVMiHbaM5E2R5QdOqI06U/EwdAkKmPQCcPf77/W7Edjqzfiflq9qS+g/s1o2VVAnTgEqBMPe6LDF8Sm6nocrGvH6MGFSelR7HJY0Nbh1xdRGDrA3N/UmFE2jju8j+01507CceMGYOeBZnyxuwHvbzgYc1JlT2ivRT3TWsTm/0SUOgxaKX7QGrpJiREfSpICQQBuWTQVAFA1rCTVMaueTQsEmWnNZl/tb8KOsNnt0SbuJeL4ieoM+okjSvTrwv96m9sjH0ObSFjbqNZ2Fud3nr4+cfIgAMA5c0b2aEw19W64vUE0tHgxbWxF13fohsrSPDS2+vTLA0tdpttthkymtgJVeC35oLI8iIKAylIXGlq9eHT5Zry0YifW7zialDEC6iQsACgK1fuWFapBa7SlbYmIeotBK0VdulLTnUyr8VSgKJgnxqRST9abp/R56E8b8b9/3mj622mNsrJUIqaPq8BzS+bDZjVmWs3bRFspKrz7xUTDjPa5UwbhuSXze7zYgXaWwe0NorggOcGa3SqiI5QRLXDZYLeZX6Pa69JqETF2SBGmjS3Hz68/wbTNvKlqMH7M6DLTr8jjl/D4a1+YVuACgHZPIOGAVjuexaEg1WG34NZFU3HlWeMT2g8RUXdwIlaOu/qciZhgyFqF0z7IYwWiQUnRl34F1A/TVAatxn17AxKK4mxL2WHxQytx2fwqnD17BGqbPBCEzjXpk6EwrHl9eNlIuyegZ1gBdYJTIhOlunLBSaPx+U61HrY4SRlG4+l/bQWsaEQByHPacPslx5ompP34ypkYE1oUobLEhSfvOBX1rV787582wBeQsHFXPTbuqoc/IOn1sbf9+mMAwPcvnILJo8uwYWcdTpwyyNRiK1yr2w8BQEFe5zGYMT55v1siIiMGrTnulGOHxL1diJJpbWrz4cDRNkwbWwFJlvVJWwBgEYSUTpAKGAKShmaPaQILZa9X369Wg9bGDpQXOVHfEll32lPHjR+A2y6eBpfdgof+tNH0NwIA1YdaTJe1YC5ZSgzZ1aIobbF6QgtaK0tdGFKRH3O7QkOwKAgC/ufa2di4qy6iU4DDbsHQinw4bBas+KyzV+1bq/dhUFmevogIADz5962d97NZMHVMecyzMa1uPwrybKb3ACKiVOE7DcVlESKD1gdf+hyPLv8CQGSmVUhxptXYZzOYpjIESlysvwG3N6Cv6KS1dOotQRAwvaoCwyvVwCt8hSatsf6sieqKVsnuI1xgyPQmqy9pgUsNflvilFPcfOEU/PcV5izs8MoCXDBvdMz72G0WuMMmw3269Qhq6t1Rt3/y71tx79NrYu6v1R1g/SoRpQ2DVopLr2k1JK+0LFlTmy8i0yqmOtNqDFp7WNPa0OJNeVuuXPGvNfuwOyyTCUBvLRWuwyfB5bDiNz86BUsXnxB1m57SVsYKz7R6/RIsooA5x6iTuJL912k8fZ6sJUu1VaR8UZZJ1hw/sRIVCZ5pcITa240LrdQ1qCwP2/c14el/fomiPBtuWjgZgJqN1ia7NbX5IvbT7gmgrcOP9zYcTHm3ECIiDcsDKC4tKRUtEF234yj++ek+8/aiYApwk0mSZby5ak/nZalnn5bPvvUlduxvxqO3nsQsUS9pfULDF3pojdElIBiUYbeKKVnqV5tRv31vE6aOKdczoD6/BIfNgpICtWNAsupOje6/5njkO21x6z8TYbOKuOS0sUnbn0ZbCrbAZcNzS+bD4wvill99BAC4aeEUvS620GXDsMoC7NjfDKtF1F//AoB31x/EK+/v0gP0QzGytEREycagleLSalqjLeP6dU1khs0iCClbEWvdjqP4YFONfjkQ7Fl0vL9WzbK2eXhqszfi9VyNdVtQkvXAKdlEUYAoCPhky2EcqGvHfVcfD0CdLe90WDBqcCGuO3cSjg+VCSST1nYqmXragise7bWp1cwa+91OHFmqB6BjhhbjrOOH4/0Nh+DxBfHgHz/H7ppWnDt3JN5arX5R1ZaGveabE5M+TiKiaFgeQHHFWxHrs+2R7XEEUV1WU1EUUxPzQFDGZ9trezWW9g7zKefn3t7eo/1oWaNogTh132sf7Y55W/jfi/blICjJsMZYajUZtGO770gbJFnG/3t2Lf756V447VaIgoB5UwdHtI/KJWcdPxyAulwzoJY23LpoKm6/5FgAwJDyPHz/wik447hhcNgsOCZUprC7phUA9ID1ktPH6vvkZEgiShcGrRSXGGUiVjw2i4imNh/Wbq/Ff/1mlT4J5h+f7MHv/rENtU0dXewhNk9YfZ8WGC1fWY3/eWFdt/cTDJUVpCojnCtWbjgU8zZtItbV50zE3MkD0er2Y8vXDerEvSRPhIpl54EWHKxTM4cThpek5TGz3cwJlXhuyXxUlnbW3s4YPwDTxpYDUIPYWRMr9QllMydGtq/6waKp+sStaWPLMWowG88RUXqwPIDiskRpeTV0QD4O1XXWsRmbss8YNwD/WrsfL/17J7x+CZt3N2Du5EF6n8ye1qECgNeQuZ05YQAOhE7z/2vt/lh3ifDSiq/0CVypnDCW67QvBFPHlOPYqgqs3laLmno3AinOtBoFguqXnHynFZefUZWWx+xvrIZJlt9ZMB5DyvMwaVQZivPt2F/bjlsvmsp2V0SUNny3obi0zyPjMq7hE1luv3Sa/nNZkTrZRVvNZ+POOrS6/XrzdW+c2dDxKIpiCk4rS1wxJ/vEcu2y9/G+ITuYrpW7coGWUddov1tRUP9eivJs8AdlNLf7UjIRSmMRBZw6Xe093Bia9X71ORPNK2hRt4mGrPjpxw3FpFFlAICxQ4vxP9fOZsBKRGnFdxyKS4hSHhAMy5Ya+1SGZ9G2fN1oKgnw+mNP3okn/FS+02GNenp/69cN2FxdH3H9tr2NEdcx09pzStjv7tm3zPXF2rHRgh6b1QJ/QEKr26/P4k+Fp+8+HVeePQEA8OI7XwGIv0wxxaedaSkrcvR4mVsiomRh0EpxdfZp7QxSfAEJeYaWRQVOQ9AalnnxBSTsPdymX+5pptUftp58nsOKoCTrp4ABYOueBjzyl8349V+/iLj/V/ubIq77/RvbejQWUjs5GO062NlJQlYU+EPHRQt67DYRze0+KIr5S04qhAdXThuroHrKElo4JNXHjIioOxi0UlzRJmL5/BJ8hiDSaQhgjatjaepaPPrPPc20+g3trZ5bMh92mwhFgWk50Ede3Rzz/pKsoKzIgd/86BT81+XTAQCNrb64Kw5RbOErKGmLCbR7AvjJ02vx9JtfAuj80mO3WtAW6v7gdKQ+82ksQbDb+DbXW6MGcbIVEWUe382pW/4QOtUKqIHn8ZM6e10aA1WrpfNP6upzJsJqEUyr+vQ201pepC796Qn1Ad1zuDXq9tcue990CluSFNitFrgcVgws7WzR8+nWwz0aT3cFgpKp9Vd/caQxeheIR5dvNt2mZVptNhFtoRrkdGQ+l3y3c3nTsqLkLBebi7RSoCmjyzI8EiIiBq3UA76AhBGVnc3UjYGqceLGvKmDYLOK2GMoD4i3LGUsiqJg6x61JlVbZnLz7gYAwOqtR2Lezx/ozM7KsqKf6jSePi4vcuKL3fUx117vrfufX4c7nliVkn1nUrQevY2tXlMpCAB9oo7DKqK5XQ1a01FjaixfyXeyPKCnpo0tx39dNh0zJ0S2viIiSjcGrZSQ+5//DB6fZFpJxxKj76ZFFGG1iDhY165f15PT8Rt21uGlFTsBdK7kozVHLymMPann5kc+xM4DzQDU8gBtnMag6Xf/2IZHl3+BnzyzNupkrd6QZQWHGzpMpRT9WSAoR0xu077EFBc49DXs0xG05hvqrJO9FGouEQUBk0eX8XdIRFmBQSt16TsLxsMiCpBlRV8C1Rh4xPtAsxm6CQwuz8OKdQcSfvxWQ6CrrWY0ILQKT/hyoSdOGWS6/GkoEyvJsp71c9mjZ95e+yD2Ck890WZoyZVoe66+6J6n1sS8zbhcrjMNK1KJooBvnzEO1507KeWPRURE6cGglbpksQiQFcWUMe1u4KGVDhQX2DG8sgCAusRmYo/f+Weq1bRq69dv3GVub1WUpwZHpaEMrDaLXZIM5QGigNmTItefT3YrplWG0oU7f/NpUvedLeYcM7Bb29kMxzBdLagWHD8c86YOTstjERFR6jFopS5ZBAGKArg9nQ3kbd2cka1lWmdPHIi5k9Us6AebYi//GY0xj6vtzzgj3Lj2uVZ7N3tSJY4ZVaqvwCXJ5uVDb1o4xfQYdquoz4BPFuOEL20Vrv5Aey4nHDPQVMMcbtmNc/Sfjf177WlaEYuIiPoXfnpQl7TAJGBYVCC8H2u4iSNK1O1CGTaLKOjrm48IZVy7yxsw9/wEzCUJpYa61tJCB5666zRcenoVLKKoN7kPykrcAGtwRT6ONnVENM3vjfBFGPqLjzbXAABmjKvA1DHlMbczrm9vzLSyPpKIiHqCQSt1SQv2jNlCY8eAcI/edhJ+dOmxADozo6IoQBAE5Dut+hKv3aW1yfp/Vx9vuv70GUMBAF8daMZ1507C8RMrUVbkhNUiQhAEWEQBUmjMkiRHLDl517dn6D8PrchHa0cg4bHF8+xbXyZtX9lCURR9UhygZlt/dt3siO2uP/8Y0+V09GYlIqL+jUErdckSJWi1RFlEQFOUZ9fXetcybFq86HJY4fElNpve6w9iQIlTr4kNH5cgAPOmDsbNF5pP+Vssgp5pNXYP0EwaWar/PHKQ2sLLm+DY4gnPtCa7/CATPvmis6+t9rsN/73eetFUvRREo9UiL5g1PMUjJCKi/opBK3VJ62saCK1KdfK0wRg5qBBnzByGSkPdZjR6pjW0jzyHNeFm+16/BGeUGf9aXe2ti6ZFvZ9FVINWWVbwxe4GNLZ6o24nABgdWvHH7U1dYLk3xkIIfcmO/c36z1ophRQWnE8YXopwWtDalgNdFIiIKDXYdZu6pGXS3li1BwBw0WljIQoCvrNgfJf31coItKycqydBa1hfWM15c0fBIoqYMib6aj1a0FrToC4csP9oe8Q2/3fziXDYLWgO9RC9//l1uGDeKFx48piExhhNRbETg8ry9IURhDg1tX2F39BztqxQDUTzDM37n1syP+r9yorUuuOuvuQQERHFwkwrdUmraa1rVjOVYgITaTpCmcu3Vu8DoAatide0BqNmWl0OKxadMiZmfa3LYUWHN4ADtZHBqqa82IkCl83UhumNVXsTGl8ssqKgMK+zP6mlH0xA0hZKGD24EBND5RVlRU7ccMExuPT0qpj3c9qtePCGOTh/3qh0DJOIiPohZlqpS+E1i4kEre0eNUA954QRANRAcvehFri9AdOqRfF4/RIKXN3b1qi0UF2FqSFUFnDhSaNjbutyJP+lIBmWjgXU2tu+Tgtahw4w1xfPOWZQtM1NBpbldbkNERFRLMy0UpfCW0V10e3KZFCZejp4wfHqBByXw4KjzR4sfWF9t/eh1rQmPvu8rNAJtzeI5nYfKoqduCBO0Gpcnz5ZwaUsKyg2rASllUj0Zb4o7ceIiIjSgUErdSk8s5pIpvXqcybhmnMmRqw2dbTZ0+19xCoP6IpWR/n+hkOmVbWiEQQBP71qFq44cxwURQ04e0uWFeQ5rHj4lnkA+kffVm1JXVsXv08iIqJk4ycPdSky09r9oDXPacXJxw7RL/ckbOtpptW46EB9N4Lk0YOL9DKEZKxgJSuK2i82VCIg9YNVsbTAe/TgogyPhIiIck1CQeuOHTtwzTXXYPbs2Zg3bx7uvvtuNDaqM6Pvu+8+TJkyBTNmzND/vfrqq/p9X3/9dSxYsADTp0/HokWLsHHjxuQ+E0qZ3tS0RuyrB/f1+oM9ak5vDFq1Fbq60tSudhE40tiR8OOF03rDalnJQD8IWsuLnRgzpAhzJg/M9FCIiCjHdDto9Xq9WLx4MWbMmIFPPvkE//znP9Hc3Ix7770XALBlyxYsXboUGzdu1P9ddtllAIC1a9di6dKlWLZsGdatW4cLLrgAN998Mzye7p8ipszpTaY1nHGmf4u7656diqLE7NPaFW2BAwC4ZdHUbt3HYVPvc7AudseB7pJDS8da9Uxr3y8P8HiDmDC8hEuxEhFR2nU7aK2pqcHEiRNxyy23wG63o7S0FJdddhnWrVsHv9+PnTt3YsqUKVHvu3z5cpx77rmYOXMmbDYbrr76apSWluLtt99O2hOh1EnmpBtjT8/u1I36AzIUBT0qDzDqbtA7e5KaQbRbe7/sqCyrvzutnvaLrxt6vc9M6/AFTceQiIgoXbr96TNmzBg888wzpuv+/e9/Y/LkydixYweCwSAee+wxfP755ygsLMRFF12ExYsXQxRFVFdX46KLLjLdt6qqCjt27EhosKIo9CrLF40WUHQ1USeX2W3mAM5q7fnv6psnjsTumlZsrq4HBPO+oh2L9lCf13yXrUeP+4cfnwEA3c4MFhXYUZxvx9eHWzFnStdtnGJRFAWyosBmFfXf39ova7ud8c20aMdCURR0eIMoyLP36m+AEsf3qezBY5E9eCyyR7qORY9SJoqi4NFHH8XKlSvx0ksvob6+HrNnz8aVV16JRx55BNu3b8ctt9wCURSxePFiuN1uuFzmlXCcTic6OhKrGywry0/ZacmiIq7UE0u731yLWVqa36v9XbZgAjZX16OgwBl1X0VFLrR7AvjvJz7Gd86eCAAYUJ7f68ftrhOPHYJNO+twy6U9fzxt0pX2HKeOrcCW3fVpew7JYnxdeHxByIqCyjQeCzLj+1T24LHIHjwW2SPVxyLhoLW9vR333HMPtm3bhpdeegkTJkzAhAkTMG/ePH2badOm4aqrrsLbb7+NxYsXw+Vywes1r/vu9XpRWhq5Rnk8jY3ulGRai4pcaG319IvZ3anQ3t557G69eBqamty92p+nQ53s1NjkhsvaeTyNx2LDV0ex/0gbfvny57BaBBQ7rb1+3O4qybOhqdXbq8fzB9V+pl6vH01NbhwzsgRf7WtM23PorWivi8bQIg2KJPWZ59Ff8H0qe/BYZA8ei+wRfixSldhIKGjdv38/rr/+egwZMgR//etfUVamrvn+7rvvor6+Hpdffrm+rd/vh9Oprk0+btw47Nq1y7Sv6upqnHLKKQkNVpaVpPTPjEaSZASD/KOPRgn9ziuKnZhRVZG035PPL0XdlyTJaO9QywICQRknTR2MPIc1bcfHYbPA65fg8wdhSWQlBQOvN7RUrQIEgzIEQYA/KOPV93bholPHJnG0qWV8XWg9Wh1WC18rGcL3qezBY5E9eCyyR6qPRbc/kVtaWnDVVVfhuOOOw7PPPqsHrIBaLvDggw9i9erVUBQFGzduxIsvvqh3D7j44ovx5ptvYs2aNQgEAnjhhRfQ0NCABQsWJP8ZUdJpE7GSleXW9hdvhagPNx3Sfz5z1rCkPG535YWWdPX5pR7v4y8rqwGovVoBoCNUm/vW6n29HF3mdIQCcU7EIiKiTOj2p8/f/vY31NTU4F//+hfeeecd020bN27EPffcg/vvvx+1tbWoqKjArbfeioULFwIA5s6di/vuu0+/vaqqCk8//TRKSkqS+mQoNbRgtTf9WY20tldP/G0Lbjj/GKxYdwA/CE1Qqqlvx78/3YMd+5sBqP1VRwwsTMrjdpfWqcDjk5DntPVoH7trWgF0LlKgLX/al+lBq4NBKxERpV+3P32uueYaXHPNNTFvv/zyy03lAeEWLlyoB7HUt2hBa7JaX7lCQU9Tmw9/encXDhxth9sbRInNghsffM+07SWnVyXlMRPhDI1vx/4mzJs6WL/+kVc3weMP4sdXzupyH4fq1JpPbQWpc04YiRWfHQAEYOXGQ5gxriJiadts1+FTs8XMtBIRUSawTwR1KdnlAcag58BRtYl/rCL6TCwXqmVan31ru35duyeArXsasftQa9T7rN9xFIeiLEhQUmAHABTl23HjwslQFOCP//4Kv/v71i7H0eENYu+R6I+XCR3eIKwW0bRoAxERUbowaKUuaWUBySoPcNgsOGnaYNN1kqzop9IzzWVYiECS1TE9888v497nyb9vxbKXN+iXSwsdcNgtmDFugH5dUZ5d//mAIcD1+SVs29MYsc8fPPoRfvbCetQmYUnZZODCAkRElEkMWqlLek1rEv9ahg8oMF3+/Ks6tHsCyXuAXigu6Awu/QE1aP1id+zVrLTJVu5QzafHF0RTmw+zJ1aaths5qLM21+PrrHF95f1dePjVTfD6g1H378+SWbEd3iDrWYmIKGMYtFKXkl0eAAAnTjWvNvXn93bBnSVBq9Ui4tbQxLBAWPa3xBDQaiTJ3AVhx74mAMDGXfWm610OK+ZNjVxlS2sl5Q3rVuByqKfhtWxvpjHTSkREmcSglbqkBasnThncxZbdlx9lVn67J3qmMRNsNvWl8eOn1uCI4fR8c7s/ohOAsazBF5BgD9XEfves8RH7jfa8baElUcNbbGktwYLB1PQmTpSHmVYiIsogBq3UJVEQ8NyS+Th9xtCk7je8RNbt7cy0LjplDE6amrwgOVHF+erMfrc3iN+GTZr61aubTJeN/Wa9viC8oVP/k0ZGrvh23omjYA8FqVpZgd0WarEVKg9Y+2Utmtt9egZ3+77IetdMYKaViIgyiUErZUxZobnlk8fbmWk978RRuPbcSekekq68yKn/rHU4mBWqUd11qMW0rbHzQVBS9NpUpz0ywCtw2fC9b0wI3U8NSrVM689eWI92TwC/f2Mbfvv3rbCHsr2vf7wnKc9JURQse+lzbNxV16P7e3zBqM+JiIgoHRi0UsbcefkMnDNnhH5ZyzTefcWMTA1JFy2jqNX2hvdXDRpqWgOSjA5vEBZR0IPRcNriCkFJxlur92Llhs7Vv2779ccA1AyvsVuDVvfalY076/CTZ9bqWVyjQFDGzoMtePy1Ldhf29at/YXf3x7jOREREaUa0yaUMQPL8nDJaVWoKHbhT//ZiZZ2PwpcNkwZU55V60ifPmMoSgodaGr1AlB7rhoZJ0rd+9SaLvenBa2SrGDDzvqo2wgC4At07tcfqqOtbexAcYE9ZsZz5cZDqKl3Y9eBZkwYYS5PMNbi7j3SlvBKY4GgrNf6EhERpRs/gSjjrKIASVbwj0/2ZE3bKwCYNrYcgDqh6vwTR+GS06tQXuSANayLwpEE+6haLer9g5KMgWWuqNtIkrlvbUCSIcky7nlqDV7+z86Y+x5SkQ8AaGr3RdzmNwTBX4WWyU3E0WYPAln0ZYKIiHILg1bKOGuWnnK+/ZJj8dyS+RBCp+ldDiumja0wtcHy+IJ4dPkXCe3XopUHBOWYCzaEB8KBoKx3F4iVnVX3re4vEIgMLo3jXr3tCA43uLs9Zm2SXDZlwImIKLdkZ7RAOUU7Xd4XWC2iqYa1wzB5bMLwku7tI5SpDcpKRPuscJecNhYAsPQP602LF8SihGLKaAsShK841t06WQB6R4TjJgzoYksiIqLU6DvRAvVbxtPtNy2alsGRdM1qEUzZRu1UPwBMH1eh/+wI9WqNvg/1ZdfU5sPnX3XO5H/g+hMitrUY6l9fWhG7LECjtd/yB8N7vsr6UrRXnDlO3XcCS5z9+q9qNtlhi/28iIiIUolBK2WcVh4wYmABzp03OsOjic9qEfXT7B5fEI+91lkaYAzowpdwDd8HAKz4bL/p+sHl+RHbKoYuAFu+jr2UrEYOBa3G8oDWDj927m/G/lq1dVdFiVpH6wvGz/IaHaxT7xs+CY2IiChd2D2AMk6r1Zw9aWCGR9I1q1XUT7Pvr23DnsOdraO0gG54ZQGuPHtCzH1o2+0ITYaaNLIUp04fAgAYOagQ+4507nP2pIF49f3qiH34/FLUbK4UCnKNAentj31i2kZb1crfRWlCNJUl0SeOERERpRozrZRxWk/U8BZN2chm6QxaG1s7Z+jfetFUjBqktpC6dH5V3Drd0kIHJgwv0etZb71oqh6wawsuPHD9CXhuyfyYp+PvfHJV1Ou1hQ6iTcTSaJO1/HG2ieb8E0fpk9KIiIjSjUErZdwxo8rw0E1zMWFESaaH0iWbVdTbPj0dqhEF1KVYy4qcePru0zB5VFmX+zEuXmBchOB7Z0/A5fOrMLAsDwDgclhw5sxh+u03LZwMAPqkrHBaeUBDqzfqAgNA52pf3c20akF6ZSmzrERElDkMWikrDOgjp53tNrV7gHFBAQDQ8o/dndxk7HdqvE9xgQNnzR6ht8ISBAFXLBiPE6cMAgBMr6pAeZGajY0WlGrlARt31eO1D3ZHfeySAgfsVhEef/ygdcvuelz9wHvYHVq21s5JWERElEEMWokSoJ2uD890JnrafNvexoS2X3zeMXhuyXzYbRZcOl+d/f+MIdOr0TKtALB2e63pMgA9+C0pdKCpzRv3MZe/uxOyouCNVXsBgEu4EhFRRvFTiCgBztDkp8P15sb8YoKlnrEWFeiOimL19P6abbURt0mGHrJWUcTKjYf0y8X5dlx37iQAaolAQ0v8oFXrMrB9XxMAtrsiIqLMYtBKlAAtcGsJa8yfaKb1lFC3gJ4YPbgIk0aqk9beWWtumyXJCqwWAcMrC1Df4jUFpi6HVR9nebETDa3xg9bw8oOxQ4t7PGYiIqLeYtBKlACtrrOlXQ1aB5erE6YSTZx+d8H4Xo1D607wl5Wd7bBqmzqwfV8Tpo2twKWnV0FWFHQYVs8yjrEwzwa3J/bKWgBgjFmPHVtumjBGRESUbuzTSpQArTzgX2v3AVBPuR9u6Eg40yoIApbdOAdy9An+XWqMkiW996k1UBTA6w/C6VDH+dHmmqj3d9os8HbRPcBYD7t5d9cLGxAREaUSUydECdDKA5pDmdaCPHWhgJ6UqFaW5mFQqLVVok4+NrK8QMuMfrm3CSX5jojbbYbesU67FV5//EyrMWhddMqYHo2TiIgoWZhpJUpAeNunApcNACAgvU33zzp+OKwWAX9+d1fEbcMG5KM8NFlLM3lUKRYcP0K/7LBb4A/IkGUFYoxZZJKhPuAbJ4yIug0REVG6MNNKlABn2NKpWhuo8L6t6eCwWSDJit78f2JocYbrz1cXINC6DEweVYr/unwGpo0t1++rPQ9fnBIBY6Y13gpfRERE6cBMK1ECwoM3u0297A9mJmgF1MDTahEhCAJmT6rE8MoCAEBHqJdstFn/WtDq9UtwOaK/DSiKgokjSnDNNyelYvhEREQJYfqEqBe0OtFABoJWrVTBF1rZSpYVWAyn+o2dA8IZA95YZFltk9VXVisjIqL+jUErUQ+VFjpgs6rBXyaCVkcoy6sFnpISvT71aLMn8r6hTOv+2raY+5dj7I+IiCgTWB5A1EP/ddl0lBU50NDqxfSq8q7vkGROu/ry9QfUgFmWlagrbS08aXTEdWWFar3r9n1NmD1pYNT9y7ICSy9W7iIiIkomZlqJeqgo3w6n3YrvLBivZ1zTyR6eaQ0rD9AMLI1sq1WUb0dFsRP5TlvM/be4fXq/VyIiokxj0ErUQ/YMrxCl1aV6DTWtiZzOLyl0oLndF/P2lna/npElIiLKNJYHEPVQppc11epS/aFMa6I1qCUFDny69Qg6vEHcdvE0/fqva1ohigICQSnjz5GIiEjDoJWohxJdujXZwjsAhHcP6Ep7h7qq16bqetP1P39xvf4zg1YiIsoWDFqJEmS1iHpD/0yPwyIKpprWaBOxYgkPcO968lM0tHpN1zFoJSKibMGglShBP1g0BV/XtGZ6GADUbKsx02osD3jwxjmwx5kgdsnpVdj2/Dr9cnjACiDmwgNERETpxk8kogRNG1uBaWMrMj0MAGpdq764gGIuD4jWNcCopMCh//zbv2813ea0W+D1S5g1sTKJoyUiIuo5Bq1EfZjdkGmVEuweUJRvx4ASJ+qavVi346jptpsunIITpw+Dt8OHYAYWTiAiIgrHgjWiPizfaYXbqy7XGmtxgXiGlOdHvb4oz87SACIiyioMWon6sEKXDe0dAQCJdw8AEDGh7BuzR8DlsGJYZfRgloiIKFOYSiHqwzbvbgAAtHb4Ey4PAICApJguTxhRgkvnV8HKrgFERJRl+MlE1IdNGlkKALj9sU8SXlwAAL518miMGFigX3bauWwrERFlJwatRH3Y3MmD9J/9ATnhpWUnjCjF/dfM1i877Tz5QkRE2YlBK1Ef5vEHTZfHDCnu1f6cDmZaiYgoOzFoJerD3J6A6fLQAT2bQKV1HdCWhiUiIso2DFqJ+rBxw0tMlxNteaW57txJALgCFhERZS9+QhH1YZNHleG5JfPxn3UHYLP1/Dvo3CmDMHfKoK43JCIiyhAGrUT9wILjh2d6CERERCnF8gAiIiIiynoMWomIiIgo6zFoJSIiIqKsx6CViIiIiLIeg1YiIiIiynoMWomIiIgo6zFoJSIiIqKsx6CViIiIiLIeg1YiIiIiynoMWomIiIgo6zFoJSIiIqKsx6CViIiIiLIeg1YiIiIiynoMWomIiIgo6zFoJSIiIqKsx6CViIiIiLIeg1YiIiIiynqCoihKpgdBRERERBQPM61ERERElPUYtBIRERFR1mPQSkRERERZj0ErEREREWU9Bq1ERERElPUYtBIRERFR1mPQSkRERERZj0ErEREREWU9Bq1ERERElPX6VdC6Y8cOXHPNNZg9ezbmzZuHu+++G42NjQCAzZs345JLLsGMGTMwf/58LF++POo+nn/+eVx55ZWm65qamrBkyRLMmzcPxx9/PK666ips37495c+nL0vVsTD61a9+hfnz56dk/P1Jqo6FLMt44okncOqpp2LGjBm45JJLsHHjxpQ/n74uVcejsbERP/rRj3DCCSfghBNOwPe//33U1NSk/Pn0ZT09Foqi4De/+Q3mz5+P4447Dueffz7eeecd/XZJkvDQQw/hxBNPxIwZM3DzzTfj6NGjaX9+fUmqjgU/vxOXqmNh1OPPb6Wf8Hg8yrx585Rf//rXis/nUxobG5Xrr79eufHGG5Xm5mZl9uzZyksvvaQEAgHl008/VWbMmKFs3rxZv7/b7VYefPBBZfz48cp3v/td075vvvlm5YYbblAaGxsVn8+nPProo8qJJ56ouN3udD/NPiGVx0Lz6aefKpMnT1ZOP/30dD2tPimVx+Lxxx9Xzj77bOXrr79WgsGg8vvf/16ZPXu24vP50v00+4xUHo8f/vCHyh133KG43W7F7XYrt99+u/K9730v3U+xz+jNsXj++eeV+fPnK9XV1Yosy8p7772nTJ06Vb/98ccfV84//3ylpqZGaWtrU26//Xbl+uuvz+TTzWqpPBb8/E5MKo+Fpjef3/0m01pTU4OJEyfilltugd1uR2lpKS677DKsW7cOK1asQElJCb7zne/AarVi7ty5OP/88/Hyyy/r91+4cCHq6urw7W9/27RfRVEgCAJ++MMforS0FHa7Hddddx3q6+uxd+/eND/LviFVx0JTX1+Pn/zkJ3GzsKRK1bGQJAl/+MMf8NOf/hSjR4+GxWLBddddh2eeeSbdT7FPSeVrY/fu3VAURf8niiJcLlc6n16f0ptj0drailtuuQVjx46FIAiYP38+xo4diw0bNgAAli9fjuuvvx6DBw9GQUEBfvzjH+Ojjz7CgQMHMvmUs1aqjgU/vxOXytcF0PvP734TtI4ZMwbPPPMMLBaLft2///1vTJ48Gbt27cL48eNN21dVVWHHjh365T/+8Y94+OGHUV5ebtpOEAT85je/wTHHHKNf98477yAvLw+jR49O0bPp21J1LAD1lPSdd96J66+/HuPGjUvdk+gnUnUs9u7di9bWVrS2tmLRokU44YQTsHjxYjgcDtjt9tQ+qT4sla+Nm2++GStXrsTMmTMxc+ZMbN26FUuXLk3dk+njenMsbrvtNixatEi/bffu3di1axcmT56MtrY2HDlyxHT/iooKFBcX46uvvkrxs+qbUnUs+PmduFQdCyA5n9/9Jmg1UhQFv/rVr7By5Ur8+Mc/htvtjsg4OJ1OdHR06JcHDRrUrX2/9957+PnPf4777ruPWYxuSPax+O1vf4vCwkJcfvnlKRtzf5XMY9Hc3AxADaIef/xxfPjhh5g8eTKuu+46tLW1pew59CfJfm3IsozLLrsMa9euxaeffooxY8bg9ttvT9Xw+5WeHAvNnj17cP311+OCCy7A8ccfD7fbDQDIy8uLuL92G8WWzGMRjp/fiUn2sUjG53e/C1rb29tx22234c0338RLL72ECRMmwOVywev1mrbzer3Iz8/v9n4VRcGTTz6JO++8E7/4xS9w4YUXJnnk/U+yj8W6devwt7/9DT//+c9TNeR+K9nHQsum/uAHP8DQoUPhdDpxxx13oL293XQqiKJL9vGoq6vDkiVLcN1116G4uBhlZWW4//77sX79emb3utCbY/H+++/jsssuw1lnnYUHHngAAPQPdY/H0+X9ySzZx0LDz+/EJftYJOvz29qre2eZ/fv34/rrr8eQIUPw17/+FWVlZQCA8ePHY9WqVaZtq6uru52e9ng8+NGPfoRdu3bh5ZdfNp1qoOhScSzeeOMNNDY24owzzgAABAIB+Hw+zJo1C7/73e8wa9as5D+RfiAVx2L06NGwWq3w+/36dcZ6SootFcejrq4OgUDAdDysVvXt3WazJXH0/UtvjsVvfvMbPPPMM/jZz36G888/X7++uLgYAwcORHV1tX4qta6uDs3NzRGnVqlTKo4FwM/vnkjFsUja53dPZpdlo+bmZuW0005TlixZokiSZLqtsbFRmTVrlvL8888rfr9fWb16tTJjxgxl9erVEft57LHHImbl3njjjcrChQuVpqamVD6FfiOVx8LotddeY/eALqTyWNx9993KWWedpRw4cEDx+XzKsmXLlJNPPlnxeDwpfU59WaqOh8/nU8444wzl5ptvVtra2pS2tjbljjvuUC6++OKIxyFVb47Fc889p8ycOVPZtm1b1H3/6le/Us477zxl//79eveAeO9luS6Vx4Kf34lJ5bEw6unnt6Ao/SMt8vzzz2PZsmVwuVwQBMF028aNG7FlyxY88MAD2LlzJ8rKyvD973/fVDCsefzxx/HZZ5/hj3/8IwBg27ZtWLRoEex2u5650Dz99NPM7kWRqmMR7m9/+xueeOIJvP/++yl5Hv1BKo+F3+/H448/jrfeegtNTU2YMmUK/t//+3+cIBdHKo/Hvn378NBDD2HDhg0QRRFz5szBkiVLUFlZmfLn1Rf19FgoioLjjz8eHo8nYtLhjTfeiJtuugmBQAC//vWv8cYbb8DtduOEE07A0qVLo06go9Qdi5NPPpmf3wlK5evCqKef3/0maCUiIiKi/qvfTcQiIiIiov6HQSsRERERZT0GrURERESU9Ri0EhEREVHWY9BKRERERFmPQSsRERERZT0GrURERESU9Ri0EhEREVHWY9BKRERERFmPQSsRERERZT0GrURERESU9Ri0EhEREVHW+/9fg24msv3jugAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 800x550 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('seaborn')\n",
    "fig,ax=plt.subplots()\n",
    "ax.plot(df_gold['date'],df_gold['Price'],lw=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6242dabc-e4b4-4a51-b2ba-fd14351f2d5a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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